Providing Trade-Off Techniques Subsets to Improve Software Testing Effectiveness: Using Evolutionary Algorithm to Support Software Testing Techniques Selection by a Web Tool

2012 ◽  
pp. 222-232 ◽  
Author(s):  
Aurélio da Silva Grande ◽  
Arilo Claudio Dias Neto ◽  
Rosiane de Freitas Rodrigues
Keyword(s):  
Evolutionary Algorithm ◽  
Software Testing ◽  
Web Tool ◽  
Trade Off ◽  
Testing Techniques ◽  
Support Software

scholarly journals Comprehensive study of software testing: Categories, levels, techniques, and types

2020 ◽  
Author(s):  
Mubarak Albarka Umar
Keyword(s):  
Software Testing ◽  
Software Quality ◽  
Testing Methods ◽  
Development Lifecycle ◽  
Software Development Lifecycle ◽  
Pros And Cons ◽  
Testing Techniques ◽  
Combination Of Methods ◽  
The Right ◽  
Comprehensive Study

<p><i>Software Testing is the process of evaluating a software program to ensure that it performs its intended purpose. Software testing verifies the safety, reliability, and correct working of software. The growing need for quality software makes software testing a crucial stage in Software Development Lifecycle. There are many methods of testing software, however, the choice of method to test a given software remains a major problem in software testing. Although, it is often impossible to find all errors in software, employing the right combination of methods will make software testing efficient and successful. Knowing these software testing methods is the key to making the right selection. This paper presents a comprehensive study of software testing methods. An explanation of Testing Categories was presented first, followed by Testing Levels (and their comparison), then Testing Techniques (and their comparison). For each Testing Levels and Testing Techniques, examples of some testing types and their pros and cons were given with a brief explanation of some of the important testing types. Furthermore, a clear and distinguishable explanation of two confused and contradictory terms (Verification and Validation) and how they relate to Software Quality was provided.</i></p>

Concolic Test Generation and the Cloud

2015 ◽  
pp. 302-322
Author(s):  
Nikolai Kosmatov
Keyword(s):  
Software Testing ◽  
Test Generation ◽  
Symbolic Execution ◽  
Major Obstacle ◽  
Testing Methods ◽  
C Programs ◽  
Security Issues ◽  
Efficient Alternative ◽  
Cloud Environments ◽  
Testing Techniques

Software testing in the cloud can reduce the need for hardware and software resources and offer a flexible and efficient alternative to the traditional software testing process. A major obstacle to the wider use of testing in the cloud is related to security issues. This chapter focuses on test generation techniques that combine concrete and symbolic execution of the program under test. Their deployment in the cloud leads to complex technical and security issues that do not occur for other testing methods. This chapter describes recent online deployment of such a technique implemented by the PathCrawler test generation tool for C programs, where the author faced, studied, and solved many of these issues. Mixed concrete/symbolic testing techniques not only constitute a challenging target for deployment in the cloud, but they also provide a promising way to improve the reliability of cloud environments. The author argues that these techniques can be efficiently used to help to create trustworthy cloud environments.

On the Application of Automated Software Testing Techniques to the Development and Maintenance of Speech Recognition Systems

2012 ◽  
pp. 30-48
Author(s):  
Daniel Bolanos
Keyword(s):  
Speech Recognition ◽  
Software Testing ◽  
Automatic Speech Recognition ◽  
Automated Testing ◽  
Automated Software Testing ◽  
Testing Framework ◽  
Methods And Techniques ◽  
Testing Techniques ◽  
Recognition Systems ◽  
Automated Software

This chapter provides practitioners in the field with a set of guidelines to help them through the process of elaborating an adequate automated testing framework to competently test automatic speech recognition systems. Through this chapter the testing process of such a system is analyzed from different angles, and different methods and techniques are proposed that are well suited for this task.

Exploring and expanding students’ success in software testing

2017 ◽  
Vol 30 (4) ◽  
pp. 927-945 ◽  
Author(s):  
Deepti Mishra ◽  
Sofiya Ostrovska ◽  
Tuna Hacaloglu
Keyword(s):  
Software Testing ◽  
Undergraduate Curriculum ◽  
Automated Testing ◽  
Difficulty Level ◽  
Functional Testing ◽  
Content Type ◽  
Testing Techniques ◽  
The Difference ◽  
Testing Field ◽  
Programming Knowledge

Purpose Testing is one of the indispensable activities in software development and is being adopted as an independent course by software engineering (SE) departments at universities worldwide. The purpose of this paper is to carry out an investigation of the performance of learners about testing, given the tendencies in the industry and motivation caused by the unavailability of similar studies in software testing field. Design/methodology/approach This study is based on the data collected over three years (between 2012 and 2014) from students taking the software testing course. The course is included in the second year of undergraduate curriculum for the bachelor of engineering (SE). Findings It has been observed that, from the performance perspective, automated testing outperforms structural and functional testing techniques, and that a strong correlation exists among these three approaches. Moreover, a strong programming background does help toward further success in structural and automated testing, but has no effect on functional testing. The results of different teaching styles within the course are also presented together with an analysis exploring the relationship between students’ gender and success in the software testing course, revealing that there is no difference in terms of performance between male and female students in the course. Moreover, it is advisable to introduce teaching concepts one at a time because students find it difficult to grasp the ideas otherwise. Research limitations/implications These findings are based on the analysis conducted using three years of data collected while teaching a course in testing. Obviously, there are some limitations to this study. For example, student’s strength in programming is calculated using the score of C programming courses taken in previous year/semester. Such scores may not reflect their current level of programming knowledge. Furthermore, attempt was made to ensure that the exercises given for different testing techniques have similar difficulty level to guarantee that the difference in success between these testing techniques is due to the inherent complexity of the technique itself and not because of different exercises. Still, there is small probability that a certain degree of change in success may be due to the difference in the difficulty levels of the exercises. As such, it is obviously premature to consider the present results as final since there is a lack of similar type of studies, with which the authors can compare the results. Therefore, more work needs to be done in different settings to draw sound conclusions in this respect. Originality/value Although there are few studies (see e.g. Chan et al., 2005; Garousi and Zhi, 2013; Ng et al., 2004) exploring the preference of testers over distinct software testing techniques in the industry, there appears to be no paper comparing the preferences and performances of learners in terms of different testing techniques.

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